1119 results about "Green building" patented technology

The invention discloses a green building intelligent lighting and energy collaborative optimization system based on multi-source data fusion. According to the system, firstly, multi-source information such as indoor and outdoor illumination, weather, personnel occupation and electricity price is subjected to weighted fusion through dynamic confidence, and an accurate real-time environment state is constructed; then, model predictive control is combined with a multi-objective optimization strategy, and a sunshade device, intelligent lighting and a heating ventilation air conditioner are cooperatively adjusted, so that the comprehensive energy consumption or operation cost is minimized on the premise that the indoor illumination and temperature comfort requirements are met; besides, the self-adaptive module continuously learns and adjusts the thermal characteristics and the use mode of the building through online model parameter correction and occupancy probability prediction, and it is ensured that the energy-saving effect is stable for a long time; the system drives each execution device through a standard building self-control interface, is easy to integrate in a newly built or reformed project, and can significantly improve the energy utilization efficiency and the indoor environment quality.

The invention discloses an intelligent welding forming method and system for a green building steel heating radiator, and the method comprises the following steps: carrying out the surface defect recognition of a steel heating radiator base material based on an AI visual inspection system, recognizing a qualified base material, and automatically matching the type of a welding material from a material database according to the material and thickness parameters of the qualified base material. Welding parameters are intelligently matched through AI visual inspection and a neural network model, a laser and friction stir hybrid welding process is combined, traditional manual operation is replaced, the welding efficiency and precision are improved, and the problems of uneven welding seams and the like are solved; welding data are analyzed in real time through a multi-mode AI model, parameters are dynamically adjusted, intelligent defect recognition and repair welding are achieved in cooperation with 3D visual inspection, and the quality stability is improved through whole-process monitoring; smoke dust is treated through an environment-friendly process, acid pickling is replaced with mechanical rust removal, efficient recycling of materials is achieved through waste recycling, a green manufacturing system is constructed, and the sustainable development requirement of green buildings is met.

The invention relates to the technical field of green building energy consumption, and discloses a green building energy consumption real-time monitoring and intelligent adjusting system based on the Internet of Things, and the system comprises an Internet of Things multi-source sensing module which integrates a building internal and external environment sensing unit and an equipment operation state collection unit, and generates a comprehensive energy consumption characteristic signal through a heterogeneous data fusion gateway; the dual-channel decision module receives the signal, the load prediction unit outputs a building cooling and heating load prediction signal and a regional energy efficiency imbalance risk signal, the energy efficiency optimization unit generates an optimal equipment adjustment strategy signal, and the dynamic adjustment unit outputs a real-time energy consumption safety threshold; the intelligent execution control module and the self-adaptive equipment regulation and control unit adjust heating and ventilation equipment parameters, the multi-equipment collaborative management unit optimizes the running state of the lighting and air conditioning equipment group and collects feedback signals, and the man-machine interaction early warning platform generates a comprehensive energy efficiency risk index. According to the system, real-time monitoring and intelligent adjustment of energy consumption of the green building are realized, and refinement and collaboration of energy consumption management are improved.

The invention relates to an intelligent generation method, system and device for a passive design scheme of a green building and a medium. The method comprises the following steps: firstly, collecting site limitation data and climate data, inputting the data into a thermal performance simulation model, and outputting building heat loss and solar heat gain distribution; based on the result, a genetic algorithm is used for optimizing parameters such as the building orientation and the window-wall ratio, and a building design parameter combination is formed through energy consumption calculation, standard judgment and iterative optimization. Then, thermal and economic parameters are extracted from the design parameters to construct a data set, the parameters are screened to generate a building layout optimization instruction, and the layout is adjusted in combination with a dynamic adaptation standard to obtain an optimization scheme. And finally, associating the optimized layout with site parameters, performing energy model optimization to form a low-carbon scheme, and coupling environment adaptability data to generate a sustainable development scheme. By means of the method, the problems that traditional design parameter optimization is low in efficiency and multiple targets are difficult to balance can be solved, layout reasonability and energy consumption control precision are improved, and low carbon of the whole life cycle of the building is assisted.

The application provides a glass curtain wall construction device based on green building, and relates to the technical field of building construction. The glass curtain wall construction device is arranged on a basket to move the glass. The glass curtain wall construction device comprises a mobile lifting support unit arranged on the basket, a sliding rod horizontally sliding and rotationally connected to the mobile lifting support unit, a horizontal driving part with a driving end connected to the sliding rod to drive the sliding rod to rotate, and a fixing assembly rotationally connected to one end of the sliding rod, wherein the fixing assembly comprises a suction cup pressing on the glass. The application also provides a construction method of the glass curtain wall construction device based on green building. The application can help the workers to relatively quickly move the glass from indoors to outdoors and complete the installation, thereby improving the problem that the workers have to exert a large amount of physical strength when installing the glass in the prior art, and the workers on the outer wall are inconvenient to exert force.

The invention relates to a large-scale language model-based solid waste cementing material intelligent design and performance prediction system, and relates to the technical field of material science and artificial intelligence, the system integrates multi-source heterogeneous data through a multi-task data set construction module, and establishes association mapping of a solid waste material formula and performance; the performance prediction module based on the large-scale language model realizes high-precision cross-modal prediction of key indexes such as compressive strength and permeability; the reverse design module generates a formula scheme conforming to chemical components and industrial constraints through dynamic embedding of material scientific rules and reinforcement learning multi-objective optimization, and forms a closed loop verification link based on physical rule verification and an experimental feedback mechanism. The research and development efficiency of the solid waste cementing material is remarkably improved, the trial and error cost and resource waste are effectively reduced, rapid conversion of laboratory achievements to industrial production is promoted, and intelligent technical support is provided for solid waste resource utilization and green building material development.

The invention discloses a high-content fly ash unfired water permeable brick and a preparation method thereof, and relates to the technical field of building materials, the unfired water permeable brick comprises the following raw materials by weight: 55-75 parts of fly ash, 20-35 parts of aggregate, 8-15 parts of a composite cementing material, 0.5-2 parts of toughening fiber, 1-3 parts of a pore regulator, 0.1-0.5 part of a surfactant, and 10-18 parts of water. Wherein the aggregate is 1-3mm waste ceramic particles and 2-5mm building recycled aggregate (1: 1-1: 2); and the rest components have specific proportions, specifications and modification requirements. According to the invention, 55-75 parts of F-type II-grade or higher high-content fly ash is matched with the waste ceramic particles and the pretreated building recycled aggregate to serve as the composite aggregate, solid waste is digested, natural resource dependence is reduced, and the method conforms to the direction of green building materials; by means of a modified composite fiber and composite gel system, the pressure resistance is larger than or equal to 25 MPa, the fracture resistance is larger than or equal to 3.5 MPa, the water permeability is larger than or equal to 1.5 * 10 cm / s, the freeze-thaw loss is smaller than or equal to 3.5%, and the grinding pit is smaller than or equal to 30 mm; through graded mixing, bidirectional pressurization and segmented maintenance, the porosity is kept to be 15%-25%, the percent of pass is increased, and the cost is reduced.

The invention discloses a project quality detection method and system based on green building design, and relates to the technical field of project quality detection. The engineering quality detection method and system based on the green building design comprises the steps that S1, BIM structured data, real-time monitoring data, structure acceptance data and construction event and window data are preprocessed; s2, on the basis of BIM structured data and in combination with a BIM model, the qualification state of the component and the quality grade of the partition are judged; s3, identifying a working condition switching anchor point and an event, and performing segmented division of a working condition process; s4, feature clustering and performance state discrimination are carried out, different working condition types are identified, and tagging management is carried out; s5, identifying dominant factors and performing attribution assignment through multi-dimensional label attribution and traceability judgment; and S6, performing grade judgment and grade response through multi-source time sequence item-by-item difference analysis. The problems of state interval disjunction and difficulty in accurate attribution and stable diagnosis caused by space-time mismatching of construction progress, BIM nodes and energy consumption environment data and data asynchronization are solved.

The invention belongs to the technical field of building construction, and discloses a green building intelligent construction platform which comprises a construction platform body and further comprises first intercepting assemblies symmetrically arranged on the two sides of the construction platform body; the second intercepting assembly is movably connected to one side of the construction platform; through cooperation of structures such as a first intercepting assembly and a second intercepting assembly, objects are prevented from falling off from the high altitude, when a U-shaped plate moves, the objects can slide along the track of an arc groove, so that a first rotating shaft drives a first baffle to overturn in the direction away from the construction platform, and through meshing connection of a second bevel gear and a first bevel gear, the objects can be intercepted from the high altitude. Therefore, the two first baffles and the second rotating shaft form an inclined blocking face on the periphery of the device, and therefore the situation that articles directly fall to the ground from the high altitude, and people and objects below are injured can be effectively avoided.

The invention discloses an all-solid-waste negative-carbon porous brick and a preparation method thereof, belongs to the technical field of green building materials for solid waste recycling and CO2 capture-storage-utilization, and particularly relates to a porous brick which takes red mud, steel slag and recycled aggregate as main raw materials, constructs a hierarchical pore structure through low-water-binder-ratio semi-dry pressing molding, and is prepared from the following raw materials in a solid-solid-waste negative-carbon porous brick. And directional carbonization curing is carried out by using cement kiln tail gas CO2 under the conditions of normal temperature and micro pressure, so that the national waste porous brick with negative carbon characteristic is prepared. According to the method, solid waste high doping, CO2 efficient solid storage and product performance synergistic improvement can be achieved.

The invention provides a green building exterior wall coating with a heat insulation function and a preparation process thereof. The method comprises the following steps: S1, determining raw material formula parameters; s2, pre-dispersing the raw materials; s3, carrying out grinding treatment on the pre-dispersed slurry; s4, mixing and blending the coating; s5, performing performance detection; and S6, packaging the qualified finished coating. Aiming at the core requirements of high heat insulation, low pollution and easy construction of the green building wall paint, the invention constructs a set of full-process preparation process integrating a multi-objective optimization algorithm and real-time feedback control, and finally realizes collaborative optimization of paint performance and production efficiency through scientific design of a raw material formula and precise control of production links.

The invention belongs to the technical field of building materials, and particularly relates to a preparation method of a biomass reinforced cement-based thermal insulation wall material and the wall material. The preparation method comprises the following steps: (1) crushing wood fibers, putting the crushed wood fibers into a NaOH solution, washing with water and drying; (2) carrying out dry mixing on cement, the modified wood fiber, nano SiO2 particles and calcium stearate; (3) diluting hydrogen peroxide with warm water, adding into the mixture, and stirring; (4) injecting the foaming slurry into a mold, and vibrating; and (5) steam curing. Through a collaborative technology of fiber surface modification, nano-particle regulation and control and hydrophobic layer construction, the comprehensive performance breakthrough of the fireproofing grade of A1 grade, the heat conductivity coefficient of 0.048-0.055 W / (m.K) and the compressive strength of 1.2-1.8 MPa is realized. The energy consumption is reduced by 70% through the low-temperature steam curing process, the proportion of agricultural waste is larger than or equal to 30%, the carbon emission intensity is smaller than or equal to 150 kgCO2 / m < 3 >, and the requirement for green buildings is met.

The invention discloses a solid waste-based low-carbon gel material and a preparation method thereof. The material comprises the following components in percentage by mass: 40%-60% of high-activity slag, 20%-35% of tower bottom ash subjected to stage treatment, 3%-8% of a pH sensitive composite exciting agent, 0.5%-2% of nano C-S-H seed crystal, 0.1%-1% of modified cellulose nanocrystals and 15%-25% of water, and the water-solid ratio is controlled to be 0.15-0.28. The preparation method comprises the steps of tower bottom ash grading pretreatment, nano C-S-H seed crystal preparation and dispersion, pH sensitive composite exciting agent preparation, mixing and slurry preparation. Sulfate release is optimized through staged treatment, alkalinity is dynamically regulated and controlled through a pH sensitive exciting agent, ordered hydration and a multi-stage pore structure are induced through nano C-S-H seed crystals and modified cellulose nanocrystals, and the compressive strength, the impermeability and the low expansion rate are remarkably improved. Industrial solid waste is effectively utilized, energy consumption and carbon emission are reduced, the problems of non-uniform hydration and expansion cracking are solved, and the method is suitable for the fields of green buildings and resource recycling.

The invention relates to the technical field of green building materials, in particular to phase-change energy-storage thermal insulation mortar and a preparation method of the phase-change energy-storage thermal insulation mortar. 25 to 40 parts of methyl palmitate; 120 to 180 parts of hydrophobic perlite; 8 to 15 parts of expanded graphite; 3-6 parts of phosphorus sheet-shaped aluminum nitride; 180 to 250 parts of sulphoaluminate cement; 60 to 100 parts of volcanic rock micro powder; 0.3 to 0.8 part of hydroxypropyl methyl cellulose; 0.6 to 1.2 parts of a polycarboxylic acid water reducing agent; 2 to 4 parts of nano aluminum oxide; 0.8 to 1.5 parts of propyl gallate; and 1-2 parts of zinc borate. Through the proportion design of the antioxidant flame-retardant microcapsules and the lightweight composite aggregate, the problems of poor thermal conductivity and insufficient durability of a traditional phase change material are solved. Through phase change material loading, interface modification and multi-component cooperative regulation, the thermal insulation performance, energy storage efficiency and structural stability are remarkably improved, and the material is suitable for the fields of building energy saving, intelligent temperature control and the like.

The invention relates to the technical field of building energy conservation and carbon emission, in particular to a building full-life-period carbon emission calculation method based on running carbon and implicit carbon, and the method specifically comprises the following steps: building carbon emission calculation models of a reference building and a design building; the whole life period of the building is divided into running carbon and implicit carbon; constructing a three-level index system, namely a total amount index, a strength index and a relative index; respectively calculating the emissions of operating carbon and implicit carbon of the two carbon emission calculation models; respectively carrying out carbon reduction calculation on the two carbon emission calculation models; calculating a total carbon emission amount index and an intensity index of the two carbon emission models, and further calculating a relative index; and judging whether the carbon emission of the designed building reaches the standard or not according to the third-level index result, and if not, readjusting. According to the method, a building full-life-period carbon emission calculation model containing running carbon and implicit carbon is constructed, the calculation precision is improved in combination with a three-level index system, and design optimization of zero-carbon buildings and green buildings can be assisted.

The invention relates to an ancient building green repair cost optimization method combined with carbon footprint analysis, and relates to the technical field of green buildings, and the method comprises the steps: obtaining the structural damage and functional decline problems of a to-be-repaired ancient building; based on the structural damage and functional decline problems of the to-be-repaired ancient building, a repair project of the to-be-repaired ancient building is determined; based on the repair project of the to-be-repaired ancient building, determining multiple repair schemes of the to-be-repaired ancient building; for each repairing scheme, determining a production carbon emission factor, a transportation carbon emission factor and a carbon emission factor of construction energy of each repairing material of the repairing scheme, and determining the carbon emission factor of the construction energy based on the production carbon emission factor, the transportation carbon emission factor and the carbon emission factor of the construction energy of each repairing material of the repairing scheme; performing carbon footprint analysis on the repairing scheme, and calculating the total carbon emission of the repairing scheme; the optimal repairing scheme is determined based on the total carbon emission of the repairing scheme, and the method has the advantage of reducing the carbon emission of ancient building repairing.

The invention relates to a multi-source solid waste-based low-carbon geopolymer cementing material as well as a preparation method and application thereof, and belongs to the technical field of geopolymer materials. The multi-source solid waste-based low-carbon geopolymer cementing material is prepared from the following components in parts by weight: 80 to 95 parts of curing base material, 5 to 20 parts of excitation component, 2 to 5 parts of regulation component and 0.5 to 2 parts of nano reinforcing agent. The invention also provides a preparation method and application of the multi-source solid waste-based low-carbon geopolymer cementing material. The multi-source solid waste-based low-carbon geopolymer cementing material prepared by the invention has the advantages of high-value utilization of solid waste resources, excellent mechanical and durability, low-carbon and efficient process and wide application scene, and provides an innovative solution for green building materials and circular economy.

The invention relates to the technical field of artificial intelligence and data processing, in particular to a building energy consumption prediction model training method and equipment, and the method specifically comprises the following steps: obtaining building structure parameters through a building information model, deploying an Internet of Things sensor to collect dynamic data, integrating the data into a building energy consumption database, and carrying out the manual marking of the data; performing space-time alignment on the acquired data, and performing interpolation, noise reduction and normalization operation to obtain a space-time incidence matrix; constructing a building energy consumption prediction model based on a space-time diagram convolutional network, and inputting the space-time incidence matrix into the model for training; and newly collected data are transmitted to the trained model to obtain a classification result of the building energy consumption. According to the invention, the building energy consumption prediction model is trained to realize efficient processing and automatic tuning of the model on data, the accuracy of the prediction result is improved, the repeated development cost is reduced, and the method is suitable for energy management systems in intelligent buildings, green buildings and smart cities.

The invention relates to the technical field of green building group intelligent control, and discloses a green building group indoor environment and energy consumption collaborative optimization method and system based on a digital twinborn model. The method comprises the following steps: acquiring original environment data of a building group; constructing a digital twinborn simulation model and outputting predicted environment data; generating a multi-target cooperative control function; generating an HVAC optimization control instruction based on MPC prediction control; executing a power redistribution task; and performing regional mapping to generate a final control instruction. The technical problems that in the prior art, a control strategy is single, equipment response dynamic characteristics are ignored, and especially under the green building group cooperative control condition, global optimization control over energy consumption and the environment cannot be achieved are solved. According to the method, the comprehensive digital twinborn model is constructed, and the multi-target collaborative optimization and distributed power modulation mechanism is combined, so that the dynamic balance control of the environmental comfort and the energy consumption cost in the complex building group is realized.

The invention relates to the technical field of information integrated management, in particular to a BIM-based green building information integrated management method and system, and the method comprises the following steps: analyzing the structural design and material specification of a green building based on imported BIM data, comparing the image data of a solid building with the image data of a BIM model, detecting the flaws and construction deviation of a green building material, and obtaining a BIM-based green building information integrated management result. And calculating a deviation degree value to obtain a structure deviation index. According to the method, through data processing and intelligent decision support, the execution efficiency of the building project is improved, and a project team is allowed to quickly and accurately identify structural defects and material problems through real-time analysis and image comparison of BIM data, so that early intervention is realized, the potential repair cost and time delay are reduced, and the construction efficiency is improved. Real-time data updating is achieved through the WebSocket technology, it is ensured that all participants obtain the latest project information at any time, and the risk management capacity of the project is further improved through automatic conflict detection and risk assessment.

The invention relates to an intelligent green building material scheduling method and system based on reinforcement learning. The method comprises the following steps: acquiring building material characteristic data; according to the building material characteristic data and preset inventory data, arranging the building materials according to the production emergency degree to obtain a basic production scheduling scheme; the basic production scheduling scheme is used for representing a production sequence of the building materials, and the production sequence is determined based on the building material characteristic data and the inventory data of the building materials; according to a preset experience database, adjusting the arrangement sequence of the building materials in the basic production scheduling scheme to obtain an optimized production scheduling scheme; the experience database comprises the basic production scheduling scheme of the historical scheduling process; the optimized production scheduling scheme is a new building material production sequence obtained by scheduling the basic production scheduling scheme according to the basic production scheduling scheme in the historical scheduling process. By adopting the method, the production scheduling decision quality can be improved.

The invention relates to the technical field of building materials, in particular to all-solid waste alkali-activated recycled concrete and a preparation method thereof. The concrete is prepared from the following raw materials in parts by weight: 360 to 500 parts of blast furnace slag, 180 to 400 parts of recycled concrete, 90 to 270 parts of recycled red bricks, 40 to 90 parts of silica fume, 30 to 90 parts of phosphogypsum, 240 to 370 parts of iron tailing sand, 350 to 420 parts of recycled concrete coarse aggregate, 200 to 400 parts of alkali activator, 10 to 30 parts of polycarboxylate superplasticizer, 20 to 50 parts of sodium tetraborate decahydrate and 300 to 500 parts of water. According to the invention, through fine proportioning and functional synergy of all the components, a solution of all-solid waste concrete with excellent mechanical properties, durability, construction performance and economical efficiency is provided, and the concrete has a wide application prospect in the fields of green buildings and solid waste recycling.

The invention provides an energy-saving and environment-friendly green building energy-saving control method and system. Intelligent energy management is realized by integrating historical energy consumption data and meteorological prediction information. The method comprises the following steps: firstly, acquiring power consumption data of a green building and generating capacity data of a self-generating module in a preset period, and calculating a corresponding average value as a benchmark reference; and the time period electricity demand and the power generation capacity of the building are estimated in combination with weather prediction data on the day, and the current-day estimated electricity consumption and generation capacity difference value is calculated. Based on the difference value and time-interval energy data, through predictive scheduling, the system identifies an energy supply and demand gap in advance, and timely starts an energy-saving measure or adjusts a power utilization strategy. The building energy utilization efficiency is effectively improved, the renewable energy potential is fully played, the daily electricity utilization cost is reduced, meanwhile, carbon emission is reduced, and organic unification of economic benefits and environmental benefits is achieved.

The invention discloses a preparation method of a hydrophobic, flame-retardant, heat-insulating and photo-thermal characteristic coating. The preparation process comprises the following steps: firstly, mixing and stirring water and a binder into slurry A, sequentially adding cement, polymethylhydrosiloxane and a flame retardant, uniformly stirring respectively, then brushing the slurry on the surface of a substrate, drying at room temperature to obtain a primary coating, and polishing the primary coating; mixing a mixed binder, water, ammonia water and a siloxane compound to form a dispersion liquid, adding an oxide and a photothermal conversion filler, uniformly stirring, spraying the composite slurry on the surface of the polished primary coating, and drying at room temperature to obtain the multifunctional coating integrating flame-retardant, heat-insulating, super-hydrophobic and photothermal conversion functions. Cooperative integration of super-hydrophobicity, flame retardance, heat insulation and photothermal conversion performance of the material is built through layer-by-layer functionalization. The multifunctional coating has wide application prospects in the fields of aerospace, ocean engineering, green buildings, power transmission lines and the like.

The invention relates to a green building photovoltaic device which comprises a sliding rod, a supporting rod, a lifting top plate, a photovoltaic frame, a sliding seat and a telescopic driving piece. The sliding rod is fixed on a foundation through a support, and a sliding seat is arranged on the sliding rod in a sliding manner; the supporting rod is located on one side of the sliding rod. The lifting top plate slidably sleeves the supporting rod, the sliding seat is fixed to the bottom of the lifting top plate and provided with a horizontal sliding hole, and a limiting rod capable of sliding in the extending direction of the horizontal sliding hole is sleeved with the horizontal sliding hole; the bottom of the photovoltaic frame is hinged to the sliding seat, the top of the photovoltaic frame is hinged to the limiting rod, a first hinge seat is arranged on the lower fixing seat, a second hinge seat is arranged at the bottom of the photovoltaic frame, and the two ends of the telescopic driving part are hinged to the first hinge seat and the second hinge seat. The invention provides a structure capable of freely adjusting the angle of a photovoltaic panel and obliquely and inwards storing the photovoltaic panel below the lifting top plate, the purpose of adjusting the angle of the photovoltaic panel can be achieved, the structure is stored when necessary, and damage to the photovoltaic panel by hail weather is avoided.

The invention belongs to the technical field of building materials, and provides a baking-free brick and a production process thereof, the baking-free brick comprises the following raw materials: 58-62% of industrial waste residue, 2.5-3.5% of stone nitrate, 8-10% of cement, 2.8-3.5% of quick lime, 0.15-0.25% of ash powder, 0.18-0.22% of JFS activator, and the balance of water; industrial solid waste resources are effectively utilized, energy consumption and production cost are reduced, exciting agent ions are promoted to diffuse to stone powder lattice defect sites through the steam heat effect, a nano water film enhances solid-liquid interface ion exchange, the material reaction activity index is remarkably increased, high-temperature sintering is not needed, and the requirement for green building material development is met; the environmental pollution is reduced.

The utility model provides a novel green building vertical plant climbing frame, which belongs to the technical field of building greening, and comprises two support frames, a climbing mechanism and an adjusting mechanism, the number of the support frames is two, the opposite side walls of the two support frames are provided with chutes, the bottom of each chute is provided with a slide rail, and the slide rails are arranged on the side walls of the two support frames. A plurality of sliding blocks are connected into the sliding groove in a sliding mode, the climbing mechanism comprises an installation base fixedly connected to the side wall of the side, away from the sliding groove, of each sliding block, a transverse rod is fixedly connected to the installation base, the climbing mechanism further comprises a supporting mechanism, and the adjusting mechanism comprises a fixing shaft fixedly connected to the sliding blocks; the fixing shafts penetrate through the sliding rails and are in sliding connection with the sliding rails, the fixing shafts are rotationally connected with connecting rods, every two adjacent connecting rods are rotationally connected through a rotating shaft, and the adjusting mechanism is driven by the driving mechanism. The distance between every two adjacent cross rods can be adjusted, practicability is high, the loading capacity of the device is high, and the service life is long.

The invention discloses a green building energy consumption adaptive regulation and control system based on dynamic environment parameters, and relates to the technical field of building energy consumption regulation and control, and the system comprises a multi-source environment sensing module which comprises a plurality of environment parameter collection devices which are arranged at different spatial positions of a building atrium area and are used for collecting various kinds of environment parameter information, generating a structured data packet; and the control analysis module is used for receiving the structured environment data packet, performing field analysis, generating a control intention set based on a preset atrium environment control rule, identifying an environment parameter conflict relationship caused by vertical spatial characteristics of the atrium, and outputting the control intention set with a conflict identifier. According to the invention, multi-point synchronous acquisition of parameters such as temperature, humidity, air quality and illumination intensity in a building atrium area is realized through environment parameter acquisition devices arranged at different spatial levels, and a comprehensive credibility weight is generated in combination with personnel quantity information to construct a structured data packet.

The invention relates to the technical field of coal gangue activation, and discloses a coal gangue activation process optimization method and system for preparing a cementing material and filling aggregate, and the method comprises the following steps: carrying out crushing, screening and sorting pretreatment on a coal gangue raw material; the pretreated coal gangue particle material is subjected to physical synergistic activation; carrying out chemical compound activation on the coal gangue particle material subjected to physical activation; sampling and detecting the coal gangue particle material subjected to composite activation; an artificial intelligence large model is constructed to analyze detection data, the activation degree is quantitatively evaluated, and the performance strength is predicted; and dynamically generating an optimization instruction aiming at preparation process parameters, and preparing the cementing material and the filling aggregate. The activation efficiency and product performance of the coal gangue are improved, high-added-value resource utilization of the coal gangue is achieved, and an effective technical support is provided for large-scale consumption of the coal gangue and development of green building materials.

The invention relates to the technical field of building energy conservation and green buildings, and discloses a design parameter optimization method for a tropical zero-carbon building integrated system. According to the method, an input correlation-output uncertainty-global sensitivity three-dimensional analysis framework is constructed, through high-fidelity simulation modeling, Latin hypercube sampling and Gaussian process proxy model construction and verification, and in combination with Pearson correlation analysis, Monte Carlo propagation and Sober sensitivity calculation, a dominant parameter set and key interaction items are accurately recognized, and the accuracy and the reliability of the system are improved. And finally, solving the optimal low-carbon parameter combination by adopting a sequential quadratic programming algorithm under the engineering constraint. The system comprises twelve functional units such as a meteorological acquisition unit, a parameter definition unit and a simulation modeling unit, and outputs a parameter list which can be directly used for enclosure construction, unit type selection and photovoltaic arrangement. According to the method, scientificity and implementability of parameterization design of the tropical zero-carbon building are improved, annual net carbon emission can be reduced through actual measurement, and intelligent decision support is provided for the building double-carbon target.